Evidence map›Paper›PMID 42080645›Full record

ArticleCancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology2026

Modeled Sojourn Time and Sensitivity for Detecting Preclinical Cancers Retrospectively by a Multicancer Early Detection Test.

James Y Dai, E Georg Luebeck, William D Hazelton, Christina A Clarke, Earl Hubbell, Alpa V Patel

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In one paragraph

Article in Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

6 authors.

James Y DaiGrail Inc , Menlo Park, California.ORCID 0000-0001-6479-9286
E Georg LuebeckPublic Health Sciences Division, Fred Hutchinson Cancer Center, Seattle, Washington.ORCID 0000-0002-4378-2829
William D HazeltonPublic Health Sciences Division, Fred Hutchinson Cancer Center, Seattle, Washington.ORCID 0000-0002-7975-5080
Christina A ClarkeGrail Inc , Menlo Park, California.ORCID 0000-0002-7515-2549
Earl HubbellGrail Inc , Menlo Park, California.ORCID 0000-0001-7301-3759
Alpa V PatelDepartment of Population Science, American Cancer Society, Atlanta, Georgia.ORCID 0000-0001-9997-1218

Funding

American Cancer Society (ACS)Grail (Grail, LLC)
6 · The paper itself

Abstract

backgroundBlood-based multicancer early detection tests have potential for clinical benefit, but key performance metrics for cancer screening, such as sojourn time and sensitivity of these tests for detecting preclinical disease, are not yet known.

methodsIn a retrospective analysis of stored plasma samples in the American Cancer Society Cancer Prevention Study 3 (CPS3), GRAIL's MCED test was evaluated for detectability prior to cancer diagnosis. Classical state-transition models for cancer screening were modified to characterize the natural history of ctDNA-shedding cancers. The sensitivity estimand for detecting preclinical cancers by the MCED test was proposed in the context of retrospective testing, and a Bayesian likelihood method was developed to estimate preclinical detectable duration and sensitivity.

resultsAnalysis of CPS3 data showed that for the 12 prespecified cancers that represent two-thirds of cancer deaths in the United States, the test had 64% estimated overall sensitivity across all stages, and 43% sensitivity during an average 1.36-year preclinical detectable window before metastasis. Untestable assumptions on state transition and sensitivity are discussed, along with limitations related to using stored plasma samples.

conclusionsState-transition models were developed for retrospective analysis of plasma samples from the CPS3. Estimates for the length of the preclinical detectable window and the sensitivity at screening support annual MCED screening to intercept late-stage cancers. IMPACT: Retrospective analysis of plasma samples from the CPS3 supports the potential of GRAIL's MCED test to detect cancers early in the preclinical state. See related In the Spotlight, p. 1484.

Indexed as

Early Detection of CancerNeoplasmsBayes TheoremBiomarkers, TumorFemaleHumansRetrospective StudiesSensitivity and SpecificityBiomarkers, Tumor

Identifiers

PMID42080645
PMCPMC13530997

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.